5 citations · 5 across the 7 of their papers we have counts for
8 papers
A Multi-Stage Framework for Kuzushiji Character Recognition in Japanese Historical Documents
Rui-Yang Ju, Kohei Yamashita, Hirotaka Kameko +1
Kuzushiji was a widely used cursive writing system in pre-modern Japan. Due to simplification and glyph variation, most modern Japanese readers cannot read Kuzushiji characters. Co…
DKDS: A Benchmark Dataset of Degraded Kuzushiji Documents with Seals for Detection and Binarization
Rui-Yang Ju, Kohei Yamashita, Hirotaka Kameko +1
Kuzushiji, a pre-modern Japanese cursive script, can currently be read and understood by only a few thousand trained experts in Japan. With the rapid development of deep learning,…
EgoOops: A Dataset for Mistake Action Detection from Egocentric Videos referring to Procedural Texts
Yuto Haneji, Taichi Nishimura, Hirotaka Kameko +7
Mistake action detection is crucial for developing intelligent archives that detect workers' errors and provide feedback. Existing studies have focused on visually apparent mistake…
BioVL-QR: Egocentric Biochemical Vision-and-Language Dataset Using Micro QR Codes
Tomohiro Nishimoto, Taichi Nishimura, Koki Yamamoto +11
This paper introduces BioVL-QR, a biochemical vision-and-language dataset comprising 23 egocentric experiment videos, corresponding protocols, and vision-and-language alignments. A…
Automatic Construction of a Large-Scale Corpus for Geoparsing Using Wikipedia Hyperlinks
Keyaki Ohno, Hirotaka Kameko, Keisuke Shirai +2
Geoparsing is the task of estimating the latitude and longitude (coordinates) of location expressions in texts. Geoparsing must deal with the ambiguity of the expressions that indi…
Towards Flow Graph Prediction of Open-Domain Procedural Texts
Keisuke Shirai, Hirotaka Kameko, Shinsuke Mori
Machine comprehension of procedural texts is essential for reasoning about the steps and automating the procedures. However, this requires identifying entities within a text and re…